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82% Off GNSS GPS IMU INS Sensors - for ADAS and Autonomous Vehicles | Udemy Review & Coupon

82% Off GNSS GPS IMU INS Sensors - for ADAS and Autonomous Vehicles | Udemy Review & Coupon


This online course on GNSS GPS IMU INS Sensors - for ADAS and Autonomous Vehicles is taught by Suchit Kr, who holds a Master's degree in Electrical Engineering and has been working in the ADAS field for several years. The course contains 11 hours of on-demand video content, 8 sections, 59 lectures, full lifetime access (on mobile and TV devices) plus a certificate of completion upon completion.

Students enrolled in this course will gain insight into various GNSS systems such as D-GNSS, DGPS, RTK, PPP, SBAS and GBAS; AHRS; Accelerometers; Gyroscopes; Magnetometers; Python; Fusion; and Raspberry-pi 4. This course will examine GNSS in depth, its importance in ADAS and autonomous vehicle test and development. Students will gain hands-on experience working with GPS sensors and Raspberry Pi 4 using Python to receive real-time GPS data. They will also investigate various applications of GNSS-based systems in both automotive and non-automotive industries. Furthermore, the course covers correction methods using Differential GNSS, DGPS, SBAS, GBAS, RTK, PPP as well as an introduction to accelerometer, gyroscope, magnetometer with mathematical understanding.

Students will gain an understanding of IMUs (Inertial Measurement Units), their role in the Inertial Navigation System and its theoretical underpinnings, Kalman filter-based fusion techniques using Kalman filters. They'll also discover AHRS (Attitude and Heading Reference System), Dual GNSS/INS systems as well as multiple case studies on various theoretical fusion techniques applied to real world scenarios with GNSS and INS data sources. Additional reference material including research literature and web links will also be provided to give students confidence using these sensor systems for ADAS/Autonomous vehicle testing/validation tasks in their work environment.

This course requires a computer with an internet connection, motivation to learn new technology, and optionally a low-cost Raspberry Pi and GPS/IMU sensor for hands-on practice. This course is ideal for anyone interested in understanding GNSS INS-based measurement technology for position, speed, time, and heading estimation - especially those involved with ADAS and autonomous vehicle development.


Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) Technology rely heavily on sensors, such as cameras, radar, lidar, and ultrasonic. These sensors provide external environmental perception around the vehicle as well as some in-vehicle perception.

Furthermore, GNSS (Global Navigation Satellite System), GPS (Global Positioning System), and INS (Inertial Navigation System) are used to locate vehicles. These sensors have numerous applications in ADAS and AD, such as vehicle localization, sensor perception validation, and validation of various ADAS functions in deterministic test sites. Furthermore, GNSS/GPS provide a highly precise time reference clock for synchronizing multi-sensor systems for algorithm development; V2X and V2V applications also benefit from these sensors.

The GNSS/GPS and INS sensors have many non-automotive applications, such as mobile phone navigation and car tracking, rail transport locomotive tracking, aviation aircraft navigation from departure to landing, maritime vessel tracking/navigating ships for precise agriculture practices; surface mining/surveying drones for precise measurements; smart infrastructure applications using drones etc.

For centimeter-level accuracy, advanced technologies are employed, such as DGNSS (Differential GNSS), DGPS (Differential GPS), SBAS (Satellite Based Augmentation System), GBAS (Ground Based Augmentation System), RTK (Real Time Kinematic), and PPP (Point Precision Positioning). Furthermore, Inertial Navigation Sensors such as Accelerometer, Gyroscope, Magnetometer can be combined with GPS/GNSS for better localization and accurate measurement when GNSS signals are unavailable.

This comprehensive course encompasses all the technologies mentioned above and provides hands-on practice in measuring real-time GPS and IMU data using low cost sensors with a Raspberry Pi 4 running Python 3.

This course introduces the fundamentals of ADAS and AD, along with SAE levels of automation. Participants will gain a comprehensive understanding of sensors such as radar, lidar, camera, and ultrasonic used in these disciplines; plus they'll get to explore numerous applications involving GNSS + INS sensors in both automotive applications as well as non-automotive ones. Furthermore, various GNSS + INS devices available on the market from high cost to low cost will be discussed.

This course provides an in-depth knowledge of GNSS technology, signal processing, pseudo-range calculation, trilateration and errors associated with it. Different coordinate systems and frames used in GNSS technology as well as latitude/longitude representation and their interconversions will be discussed. Furthermore, NMEA-0183 message structures for GPS measurement along with real-time GPS measurement using a low cost device paired with Raspberry Pi 4 running Python 3 will be covered.

Participants will gain knowledge about various differential correction methods, such as DGNSS, DGPS, SBAS, GBAS, RTK and PPP. Furthermore, the course introduces the basics of IMU (Inertial Measurement Unit) operation including its components: accelerometer, gyroscope and magnetometer. They'll get hands-on experience using a low cost IMU with Raspberry Pi 4 running Python 3.

The course explores INS (Inertial Navigation System) through a case study of pedestrian dead reckoning using this technology. Participants will also gain knowledge about AHRS (Attitude and Heading Reference System), GNSS-aided INS technology, and Dual GNSS-aided INS technology. Finally, case studies drawn from research papers will help participants comprehend how GNSS and INS can be utilized in ADAS, AD, and robotics applications.


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Customer Reviews

Based on 1 review
Good course and presentation.

The use of easily understandable language to explain concepts is commendable. Thank you, Suchit.

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